code: def _train_model(model):
      loss_fn = tf.keras.losses.SparseCategoricalCrossentropy(
          from_logits=True
      )
  
      model.compile(
          optimizer="adam", loss=loss_fn, metrics=["accuracy"]
      )
  
      (x_train, y_train), _ = _get_dataset()
  
      model.fit(x_train, y_train, epochs=1)
  
file_path: model-optimization/tensorflow_model_optimization/python/core/common/keras/compression/algorithms/different_training_and_inference_test.py
imports: import os
  import tempfile
  import tensorflow
  from tensorflow_model_optimization.python.core.common.keras.compression.algorithms import different_training_and_inference
  from tensorflow_model_optimization.python.core.keras.testing import test_utils_mnist
label_desc: Use image node_id 3 for calling a global function with example usage: _train_model(model) without return types